SoroushVahidi/scidocs huggingface dataset:
Cryptanalytic Attacks on MIFARE Classic Protocol
(2013)

MIFARE Classic is the most widely used contactless smart card in the world. It implements a proprietary symmetric-key mutual authentication protocol with a dedicated reader and a proprietary stream cipher algorithm known as CRYPTO1, both of which have been reverse engineered. The existing attacks in various scenarios proposed in the literature demonstrate that MIFARE Classic does not offer the desired 48-bit security level. The most practical scenario is the card-only scenario where a fake, emulated reader has a wireless access to a genuine card in the on-line stage of the attack. The most effective known attack in the card-only scenario is a differential attack, which is claimed to require about 10 seconds of average on-line time in order to reconstruct the secret key from the card. This paper presents a critical comprehensive survey of currently known attacks on MIFARE Classic, puts them into the right perspective in light of the prior art in cryptanalysis, and proposes a number of improvements. It is shown that the differential attack is incorrectly analyzed and is optimized accordingly. A new attack of a similar, differential type is also introduced. In comparison with the optimized differential attack, it has a higher success probability of about 0.906 and a more than halved on-line time of about 1.8 seconds.
NEXMark – A Benchmark for Queries over Data Streams DRAFT
(2002)

A lot of research has focused recently on executing queries over data streams. This recent attention is due to the large number of data streams available, and the desire to get answers to queries on these streams in real time. There are many sources of data streams: environmental sensor networks, network routing traces, financial transactions and cell phone call records. Many systems are currently under development to execute queries over data streams [BW01, CCC02, MF02, NDM00, SH98]. Further, many ideas have been presented to improve the execution of queries over data streams [ABB02, MSHR02, TMSF02]. It is important to be able to measure the effectiveness of this work. To this end, we present the Niagara Extension to XMark benchmark (NEXMark). This is a work in progress. We are circulating it now for feedback. We have three goals: To define a benchmark, to provide stream generators, and to define metrics for measuring queries over continuous data streams. The XMark benchmark [SWK01] is designed to measure the performance of XML repositories. The benchmark provides a data generator that models the state of an auction in XML format, and various queries over the generated data. An abbreviated schema for XMark is shown in Figure 1.
A wearable 12-lead ECG acquisition system with fabric electrodes
(2017)

Continuous electrocardiogram (ECG) monitoring is significant for prevention of heart disease and is becoming an important part of personal and family health care. In most of the existing wearable solutions, conventional metal sensors and corresponding chips are simply integrated into clothes and usually could only collect few leads of ECG signals that could not provide enough information for diagnosis of cardiac diseases such as arrhythmia and myocardial ischemia. In this study, a wearable 12-lead ECG acquisition system with fabric electrodes was developed and could simultaneously process 12 leads of ECG signals. By integrating the fabric electrodes into a T-shirt, the wearable system would provide a comfortable and convenient user interface for ECG recording. For comparison, the proposed fabric electrode and the gelled traditional metal electrodes were used to collect ECG signals on a subject, respectively. The approximate entropy (ApEn) of ECG signals from both types of electrodes were calculated. The experimental results show that the fabric electrodes could achieve similar performance as the gelled metal electrodes. This preliminary work has demonstrated that the developed ECG system with fabric electrodes could be utilized for wearable health management and telemedicine applications.
Local Rademacher Complexity Bounds based on Covering Numbers
(2016)

This paper provides a general result on controlling local Rademacher complexities, which captures in an elegant form to relate the complexities with constraint on the expected norm to the corresponding ones with constraint on the empirical norm. This result is convenient to apply in real applications and could yield refined local Rademacher complexity bounds for function classes satisfying general entropy conditions. We demonstrate the power of our complexity bounds by applying them to derive effective generalization error bounds.
Movie recommendation system using clustering and pattern recognition network
(2018)

As the world is going global, people have a lot to choose from when it comes to movies. There are different genres, cultures and languages to choose from in the world of movies. This arises the issue of recommending movies to users in automated systems. So far, a decent number of works has been done in this field. But there is always room for renovation. This paper proposed a machine learning approach to recommend movies to users using K-means clustering algorithm to separate similar users and creating a neural network for each cluster.
Role and users' approach to social networking sites (SNSs): a study of universities of North India
(2015)

Purpose – The purpose of this paper is to evaluate and assess the awareness and extent of the use of social networking sites (SNSs) by the students and research scholars of universities of North India. Design/methodology/approach – The study is a questionnaire-based survey on the usage of SNSs among the students and research scholars of the universities of North India. The data of the study were collected through questionnaires, which were personally distributed to the identified population, i.e. undergraduate students, postgraduate students and research scholars, by the authors. The survey was based on a sample of 610 questionnaires; of which, 486 questionnaires were received, having a response rate of 79.67 per cent. Findings – The study showed that all the respondents were found to be aware of and making use of such applications in their academic affairs. It was revealed from the study that Facebook is the most popular SNS by all categories of respondents. To determine the purpose of SNSs, it emerged that SNSs are mostly used for entertainment and communication. The study also found that the majority of respondents were aware about the security aspects of SNSs. It signifies that excessive time consumption and fear of misusing personal information were the major hurdles in the way of accessing SNSs. Research limitations/implications – The study covers the students and research scholars of select universities of North India. It also signifies the use of SNSs in their research and academic environment. Originality/value – The paper provides reliable and authentic data. The study is worth, justifiable and enlightens the salient findings on the topic, which will be very useful for researchers in this area.
A Tour of Reinforcement Learning: The View from Continuous Control
(2018)

This manuscript surveys reinforcement learning from the perspective of optimization and control with a focus on continuous control applications. It surveys the general formulation, terminology, and typical experimental implementations of reinforcement learning and reviews competing solution paradigms. In order to compare the relative merits of various techniques, this survey presents a case study of the Linear Quadratic Regulator (LQR) with unknown dynamics, perhaps the simplest and best-studied problem in optimal control. The manuscript describes how merging techniques from learning theory and control can provide non-asymptotic characterizations of LQR performance and shows that these characterizations tend to match experimental behavior. In turn, when revisiting more complex applications, many of the observed phenomena in LQR persist. In particular, theory and experiment demonstrate the role and importance of models and the cost of generality in reinforcement learning algorithms. This survey concludes with a discussion of some of the challenges in designing learning systems that safely and reliably interact with complex and uncertain environments and how tools from reinforcement learning and control might be combined to approach these challenges.
Markov Games as a Framework for Multi-Agent Reinforcement Learning
(1994)

In the Markov decision process (MDP) formalization of reinforcement learning, a single adaptive agent interacts with an environment defined by a probabilistic transition function. In this solipsistic view, secondary agents can only be part of the environment and are therefore fixed in their behavior. The framework of Markov games allows us to widen this view to include multiple adaptive agents with interacting or competing goals. This paper considers a step in this direction in which exactly two agents with diametrically opposed goals share an environment. It describes a Q-learning-like algorithm for finding optimal policies and demonstrates its application to a simple two-player game in which the optimal policy is probabilistic.
Prioritized Experience Replay
(2016)

Experience replay lets online reinforcement learning agents remember and reuse experiences from the past. In prior work, experience transitions were uniformly sampled from a replay memory. However, this approach simply replays transitions at the same frequency that they were originally experienced, regardless of their significance. In this paper we develop a framework for prioritizing experience, so as to replay important transitions more frequently, and therefore learn more efficiently. We use prioritized experience replay in the Deep Q-Network (DQN) algorithm, which achieved human-level performance in Atari games. DQN with prioritized experience replay achieves a new state-of-the-art, outperforming DQN with uniform replay on 42 out of 57 games.
Deep reinforcement learning with experience replay based on SARSA
(2016)

SARSA, as one kind of on-policy reinforcement learning methods, is integrated with deep learning to solve the video games control problems in this paper. We use deep convolutional neural network to estimate the state-action value, and SARSA learning to update it. Besides, experience replay is introduced to make the training process suitable to scalable machine learning problems. In this way, a new deep reinforcement learning method, called deep SARSA is proposed to solve complicated control problems such as imitating human to play video games. From the experiments results, we can conclude that the deep SARSA learning shows better performances in some aspects than deep Q learning.
Delay Analysis of Hybrid WiFi-LiFi System
(2015)

Heterogeneous wireless networks are capable of effectivel y leveraging different access technologies to provide a wid e variety of coverage areas. In this paper, the coexistence of WiFi and visible light communication (VLC) is investigated as a para digm. The delay of two configurations of such heterogeneous system has been evaluated. In the first configuration, the non-aggregat ed system, any request is either allocated to WiFi or VLC. While in the se cond configuration, the aggregated system, each request is s plit into two pieces, one is forwarded to WiFi and the other is forw arded to VLC. Under the assumptions of Poisson arrival proce ss of requests and the exponential distribution of requests si ze, it is mathematically proved that the aggregated system p rovides lower minimum average system delay than that of the non-aggregate d system. For the non-aggregated system, the optimal traffic allo ation ratio is derived. For the aggregated system, an efficient sol ution for the splitting ratio is proposed. Empirical result show that the solution proposed here incurs a delay penalty (less than 3%) over the optimal result.
Characterization of defense mechanisms against distributed denial of service attacks
(2004)

We propose a characterization of distributed denial-of-s ervice (DDOS) defenses where reaction points are network-based and attack responses are active. The purpose is to provide a framework for comparing the performance and deployment of DDOS defenses. We identify the characteristics in attack detection algorithms and a ttack responses by reviewing defenses that have appeared in the literature. We expect that this char a terization will provide practitioners and academia insights into deploying DDOS defense as network services.
Beamforming for MIMO-OFDM Wireless Systems
(2015)

The smart antennas are widely used for wireless com munication, because it has a ability to increase th coverage and capacity of a communication system. Smart anten na performs two main functions such as direction of arrival estimation (DOA) and beam forming. Using beam formi ng algorithm smart antenna is able to form main bea m towards desired user and null in the direction of i nterfering signals. In this project Direction of ar rival (DOA) is estimated by using MUSIC algorithm. Receive Beam fo r ing is performed by using LMS and LLMS algorithm .In this Paper, in order to perform secure transmission of signal over wireless communication we have used chaotic sequences. This paper evaluates the performance of B am forming with and without LMS and LLMS algorith m for MIMO-OFDM wireless system. The simulations are carr ied out using MATLAB.
A comparison of the Two One-Sided Tests Procedure and the Power Approach for assessing the equivalence of average bioavailability
(1987)

The statistical test of the hypothesis of no difference between the average bioavailabilities of two drug formulations, usually supplemented by an assessment of what the power of the statistical test would have been if the true averages had been inequivalent, continues to be used in the statistical analysis of bioavailability/bioequivalence studies. In the present article, this Power Approach (which in practice usually consists of testing the hypothesis of no difference at level 0.05 and requiring an estimated power of 0.80) is compared to another statistical approach, the Two One-Sided Tests Procedure, which leads to the same conclusion as the approach proposed by Westlake (2) based on the usual (shortest) 1–2α confidence interval for the true average difference. It is found that for the specific choice of α=0.05 as the nominal level of the one-sided tests, the two one-sided tests procedure has uniformly superior properties to the power approach in most cases. The only cases where the power approach has superior properties when the true averages are equivalent correspond to cases where the chance of concluding equivalence with the power approach when the true averages are notequivalent exceeds 0.05. With appropriate choice of the nominal level of significance of the one-sided tests, the two one-sided tests procedure always has uniformly superior properties to the power approach. The two one-sided tests procedure is compared to the procedure proposed by Hauck and Anderson (1).
Speech recognition for vocalized and subvocal modes of production using surface EMG signals from the neck and face
(2008)

We report automatic speech recognition accuracy for individual words using eleven surface electromyographic (sEMG) recording locations on the face and neck during three speaking modes: vocalized, mouthed, and mentally rehearsed. An HMM based recognition system was trained and tested on a 65 word vocabulary produced by 9 American English speakers in all three speaking modes. Our results indicate high sEMG-based recognition accuracy for the vocalized and mouthed speaking modes (mean rates of 92.1% and 86.7% respectively), but an inability to conduct recognition on mentally rehearsed speech due to a lack of sufficient sEMG activity.
Avoiding Traffic Jam Using Ant Colony Optimization - A Novel Approach
(2007)

Ant colony optimization (ACO) is a meta-heuristic based on colony of artificial ants which work cooperatively, building solutions by moving on the problem graph and by communicating through artificial pheromone trails mimicking real ants. One of the active research directions is the application of ACO algorithms to solve dynamic shortest path problems. Solving traffic jams is one such problem where the cost i.e. time to travel increases during rush hours resulting in tremendous strain on daily commuters and chaos. This paper describes a new approach-DSATJ (Dynamic System for Avoiding Traffic Jam) which aims at choosing an alternative optimum path to avoid traffic jam and then resuming that same path again when the traffic is regulated. The approach is inspired by variants of ACO algorithms. Traffic jam is detected through pheromone values on edges which are updated according to goodness of solution on the optimal tours only. Randomness is introduced in the probability function to ensure maximum exploration by ants. Experiments were carried out with the partial road map of North-West region of Delhi, India, to observe the performance of our approach.
RF modules (Tx-Rx) with multifunctional MMICs
(2017)

Next generation RF sensor modules for multifunction active electronically steered antenna (AESA) systems will need a combination of different operating modes, such as radar, electronic warfare (EW) functionalities and communications/datalinks within the same antenna frontend. They typically operate in C-Band, X-Band and Ku-Band and imply a bandwidth requirement of more than 10 GHz. For the realisation of modern active electronically steered antennas, the transmit/receive (T/R) modules have to match strict geometry demands. A major challenge for these future multifunction RF sensor modules is dictated by the half-wavelength antenna grid spacing, that limits the physical channel width to < 12 mm or even less, depending on the highest frequency of operation with accordant beam pointing requirements. A promising solution to overcome these geometry demands is the reduction of the total monolithic microwave integrated circuit (MMIC) chip area, achieved by integrating individual RF functionalities, which are commonly achieved through individual integrated circuits (ICs), into new multifunctional (MFC) MMICs. Various concepts, some of them already implemented, towards next generation RF sensor modules will be discussed and explained in this work.
Context-Dependent Sentiment Analysis in User-Generated Videos
(2017)

Multimodal sentiment analysis is a developing area of research, which involves the identification of sentiments in videos. Current research considers utterances as independent entities, i.e., ignores the interdependencies and relations among the utterances of a video. In this paper, we propose a LSTM-based model that enables utterances to capture contextual information from their surroundings in the same video, thus aiding the classification process. Our method shows 5-10% performance improvement over the state of the art and high robustness to generalizability.
A dimmable charge-pump ZVS led driver with PFC
(2015)

This paper presents a dimmable charge-pump driver to power light-emitting diodes (LEDs) with power factor correction (PFC) and Zero Voltage Switching (ZVS). The proposed LED driver does not utilize electrolytic capacitors, providing a high useful lifetime, and it can stabilize the output current in open loop control without needing current sensors, which reduces the cost. The output power is proportional to the switching frequency, which allows the LEDs dimming. A prototype with 22 W was implemented and experimental results were discussed. The prototype presented a power factor of 0.996 and an efficiency of 89.5 %. The driver output power was reduced by more than 40% through the switching frequency while varying of 53 kHz to 30 kHz and the converter has continues to operate in ZVS.
The Bilingual's Language Modes.
(2001)

GROSJEAN 2 Bilinguals who have reflected on their bilingualism will often report that they change their way of speaking when they are with monolinguals and when they are with bilinguals. Whereas they avoid using their other language with the former, they may call on it for a word or a sentence with the latter or even change over to it completely. In addition, bilinguals will also report that, as listeners, they are sometimes taken by surprise when they are spoken to in a language that they did not expect. Although these reports are quite anecdotal, they do point to an important phenomenon, language mode, which researchers have been alluding to over the years. For example, Weinreich (1966) writes that when speaking to a monolingual, the bilingual is subject to interlocutory constraint which requires that he or she limit interferences (Weinreich uses this as a cover term for any element of the other language) but when speaking to another bilingual, there is hardly any limit to interferences; forms can be transferred freely from one language to the other and often used in an unadapted way. A few years later, Hasselmo (1970) refers to three sets of "norms" or "modes of speaking" among Swedish-English bilinguals in the United States: English only for contact with English monolinguals, American Swedish with some bilinguals (the main language used is Swedish), and Swedish American with other bilinguals (here the main language is English). In the latter two cases, code-switching can take place in the other language. The author also notes that there exists two extremes in the behavior of certain bilinguals, one extreme involves minimal and the other maximal code-switching. A couple of years later, Clyne (1972) talks of three communication possibilities in bilingual discourse: in the first, both codes are used by both speakers; in the second, each one uses a different code but the two understand both codes; and, in the third, only one of the two speakers uses and understands both codes whereas the other speaker is monolingual in one of the codes. Finally, Baetens Beardsmore (1982) echoes these views when he writes that bilinguals in communication with other bilinguals may feel free to use both of their language repertoires. However, the same bilingual speakers in conversation with monoglots may not feel the same liberty and may well attempt to maximize alignment on monoglot norms by consciously reducing any formal "interference" features to …
A Bottom-Up Approach to Sentence Ordering for Multi-Document Summarization
(2006)

Ordering information is a difficult but important task for applications generating naturallanguage texts such as multi-document summarization, question answering, and conceptto-text generation. In multi-document summarization, information is selected from a set of source documents. However, improper ordering of information in a summary can confuse the reader and deteriorate the readability of the summary. Therefore, it is vital to properly order the information in multi-document summarization. We present a bottom-up approach to arrange sentences extracted for multi-document summarization. To capture the association and order of two textual segments (e.g. sentences), we define four criteria: chronology, topical-closeness, precedence, and succession. These criteria are integrated into a criterion by a supervised learning approach. We repeatedly concatenate two textual segments into one segment based on the criterion, until we obtain the overall segment with all sentences arranged. We evaluate the sentence orderings produced by the proposed method and numerous baselines using subjective gradings as well as automatic evaluation measures. We introduce the average continuity, an automatic evaluation measure of sentence ordering in a summary, and investigate its appropriateness for this task.